Amplitude Variation with Angle Inversion for New Parameterized Porosity and Fluid Bulk Modulus

Estimating porosity and fluid bulk modulus is an important goal of reservoir characterization. Based on the model of fluid substitution, we first propose a simplified bulk modulus of a saturated rock as a function of bulk moduli of minerals and fluids, in which we employ an empirical relationship to replace the bulk modulus of dry rock with that of minerals and a new parameterized porosity. Using the simplified bulk modulus, we derive a PP-wave reflection coefficient in terms of the new parameterized porosity and fluid bulk modulus. Focusing on reservoirs embedded in rocks whose lithologies are similar, we further simplify the derived reflection coefficient and present elastic impedance that is related to porosity and fluid bulk modulus. Based on the presented elastic impedance, we establish an approach of employing seismic amplitude variation with offset/angle to estimate density, new parameterized porosity, and fluid bulk modulus. We finally employ noisy synthetic seismic data and real datasets to verify the stability and reliability of the proposed inversion approach. Test on synthetic seismic data illustrates that the proposed inversion approach can produce stable inversion results in the case of signal-to-noise ratio (SNR) of 2, and applying the approach to real datasets, we conclude that reliably results of porosity and fluid bulk modulus are obtained, which is useful for fluid identification and reservoir characterization.

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Elastic-Impedance-Based Fluid/Porosity Term and Fracture Weaknesses Inversion in Transversely Isotropic Media with a Tilted Axis of Symmetry

Geofluids ◽

10.1155/2020/7026408 ◽

2020 ◽

Vol 2020 ◽

pp. 1-17

Author(s):

Xinpeng Pan ◽

Lin Li ◽

Guangzhi Zhang ◽

Yian Cui

Keyword(s):

Reflection Coefficient ◽

Seismic Data ◽

Wave Reflection ◽

Transversely Isotropic ◽

Unknown Parameters ◽

Fluid Identification ◽

Pp Wave ◽

Axis Of Symmetry ◽

Dip Angle ◽

Elastic Impedance

The rock containing a set of tilted fractures is equivalent to a transversely isotropic (TTI) medium with a tilted axis of symmetry. To implement fluid identification and tilted fracture detection, we propose an inversion approach of utilizing seismic data to simultaneously estimate parameters that are sensitive to fluids and tilted fractures. We first derive a PP-wave reflection coefficient and elastic impedance (EI) in terms of the dip angle, fluid/porosity term, shear modulus, density, and fracture weaknesses, and we present numerical examples to demonstrate how the PP-wave reflection coefficient and EI vary with the dip angle. Based on the information of dip angle of fractures provided by geologic and well data, we propose a two-step inversion approach of utilizing azimuthal seismic data to estimate unknown parameters involving the fluid/porosity term and fracture weaknesses: (1) the constrained sparse spike inversion (CSSI) for azimuthally anisotropic EI data and (2) the estimation of unknown parameters with the low-frequency constrained regularization term. Synthetic and real data demonstrate that fluid and fracture parameters are reasonably estimated, which may help fluid identification and fracture characterization.

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Improved estimation of elastic attributes from prestack seismic data for reservoir characterization

Geophysics ◽

10.1190/geo2019-0188.1 ◽

2020 ◽

Vol 85 (1) ◽

pp. R41-R53

Author(s):

Yijie Zhou ◽

Franklin Ruiz ◽

Yequan Chen ◽

Fan Xia

Keyword(s):

Nonlinear Optimization ◽

Seismic Data ◽

Reservoir Characterization ◽

Layer Structure ◽

High Sensitivity ◽

Optimization Techniques ◽

Earth Model ◽

L1 Norm ◽

Linear Inversion ◽

Elastic Impedance

Seismic derivable elastic attributes, e.g., elastic impedance, lambda-rho, mu-rho, and Poisson impedance (PI), are routinely being used for reservoir characterization practice. These attributes could be derived from inverted [Formula: see text], [Formula: see text], and density, and usually indicate high sensitivity to reservoir lithology and fluid. Due to the high sensitivity of such elastic attributes, errors or measurement noise associated with the acquisition, processing, and inversion of prestack seismic data will propagate through the inversion products, and will lead to even larger errors in the computed attributes. To solve this problem, we have developed a two-step cascade workflow that combines linear inversion and nonlinear optimization techniques for the improved estimation of elastic attributes and better prediction and delineation of reservoir lithology and fluids. The linear inversion in the first step is an inversion scheme with a sparseness assumption, based on L1-norm regularization. This step is used to select the major reflective layer locations, followed in the second step by a nonlinear optimization process with the predefined layer structure. The combination of these two procedures produces a reasonable blocky earth model with consistent elastic properties, including the ones that are sensitive to reservoir lithology and fluid change, and thus provides an accurate approach for seismic reservoir characterization. Using PI, as one of the target elastic attributes, as an example, this workflow has been successfully applied to synthetic and field data examples. The results indicate that our workflow improves the estimation of elastic attributes from the noisy prestack seismic data and may be used for the identification of the reservoir lithology and fluid.

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Reservoir characterization over the Lille Prinsen and Ivar Aasen fields in the Norwegian North Sea using ocean-bottom-node seismic data — A case study

Interpretation ◽

10.1190/int-2020-0241.1 ◽

2021 ◽

pp. 1-64

Author(s):

Satinder Chopra ◽

Ritesh Kumar Sharma ◽

Mikal Trulsvik ◽

Adriana Citlali Ramirez ◽

David Went ◽

...

Keyword(s):

North Sea ◽

Seismic Data ◽

Reservoir Characterization ◽

Water Saturation ◽

Late Triassic ◽

Ocean Bottom ◽

Impedance Inversion ◽

High Area ◽

Elastic Impedance

An integrated workflow is proposed for estimating elastic parameters within the Late Triassic Skagerrak Formation, the Middle Jurassic Sleipner and Hugin Formations, the Paleocene Heimdal Formation and Eocene Grid Formation in the Utsira High area of the Norwegian North Sea. The proposed workflow begins with petrophysical analysis carried out at the available wells. Next, model-based prestack simultaneous impedance inversion outputs were derived, and attempts were made to estimate the petrophysical parameters (volume of shale, porosity, and water saturation) from seismic data using extended elastic impedance. On not obtaining convincing results, we switched over to multiattribute regression analysis for estimating them, which yielded encouraging results. Finally, the Bayesian classification approach was employed for defining different facies in the intervals of interest.

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Anisotropic 3D elastic full-wavefield inversion to directly estimate elastic properties and its role in interpretation

The Leading Edge ◽

10.1190/tle40040277.1 ◽

2021 ◽

Vol 40 (4) ◽

pp. 277-286

Author(s):

Haiyang Wang ◽

Olivier Burtz ◽

Partha Routh ◽

Don Wang ◽

Jake Violet ◽

...

Keyword(s):

Elastic Properties ◽

Seismic Data ◽

Reservoir Characterization ◽

P Wave ◽

Quality Estimation ◽

Amplitude Variation ◽

Linear Inversion ◽

Amplitude Variation With Offset ◽

P Wave Velocity ◽

Wavefield Inversion

Elastic properties from seismic data are important to determine subsurface hydrocarbon presence and have become increasingly important for detailed reservoir characterization that aids to derisk specific hydrocarbon prospects. Traditional techniques to extract elastic properties from seismic data typically use linear inversion of imaged products (migrated angle stacks). In this research, we attempt to get closer to Tarantola's visionary goal for full-wavefield inversion (FWI) by directly obtaining 3D elastic properties from seismic shot-gather data with limited well information. First, we present a realistic 2D synthetic example to show the need for elastic physics in a strongly elastic medium. Then, a 3D field example from deepwater West Africa is used to validate our workflow, which can be practically used in today's computing architecture. To enable reservoir characterization, we produce elastic products in a cascaded manner and run 3D elastic FWI up to 50 Hz. We demonstrate that reliable and high-resolution P-wave velocity can be retrieved in a strongly elastic setting (i.e., with a class 2 or 2P amplitude variation with offset response) in addition to higher-quality estimation of P-impedance and VP/VS ratio. These parameters can be directly used in interpretation, lithology, and fluid prediction.

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Prestack waveform inversion of three-dimensional seismic data — An example from the Rock Springs Uplift, Wyoming, USA

Geophysics ◽

10.1190/geo2016-0079.1 ◽

2017 ◽

Vol 82 (1) ◽

pp. B1-B12 ◽

Cited By ~ 5

Author(s):

Josiane Pafeng ◽

Subhashis Mallick ◽

Hema Sharma

Keyword(s):

Seismic Data ◽

Reservoir Characterization ◽

Waveform Inversion ◽

Three Dimensional ◽

Seismic Inversion ◽

Amplitude Variation ◽

Amplitude Variation With Offset ◽

Seismic Waveform ◽

Rock Springs Uplift ◽

Rock Springs

Applying seismic inversion to estimate subsurface elastic earth properties for reservoir characterization is a challenge in exploration seismology. In recent years, waveform-based seismic inversions have gained popularity, but due to high computational costs, their applications are limited, and amplitude-variation-with-offset/angle inversion is still the current state-of-the-art. We have developed a genetic-algorithm-based prestack seismic waveform inversion methodology. By parallelizing at multiple levels and assuming a locally 1D structure such that forward computation of wave equation synthetics is computationally efficient, this method is capable of inverting 3D prestack seismic data on parallel computers. Applying this inversion to a real prestack seismic data volume from the Rock Springs Uplift (RSU) located in Wyoming, USA, we determined that our method is capable of inverting the data in a reasonable runtime and producing much higher quality results than amplitude-variation-with-offset/angle inversion. Because the primary purpose for seismic data acquisition at the RSU was to characterize the subsurface for potential targets for carbon dioxide sequestration, we also identified and analyzed some potential primary and secondary storage formations and their associated sealing lithologies from our inversion results.

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Interpretation of full-azimuth broadband land data from Saudi Arabia and implications for improved inversion, reservoir characterization, and exploration

Interpretation ◽

10.1190/int-2013-0065.1 ◽

2013 ◽

Vol 1 (2) ◽

pp. T167-T176 ◽

Cited By ~ 8

Author(s):

Brian P. Wallick ◽

Luis Giroldi

Keyword(s):

Saudi Arabia ◽

Seismic Data ◽

Acoustic Impedance ◽

Reservoir Characterization ◽

Signal To Noise Ratio ◽

Low Frequency ◽

Gas Field ◽

Frequency Model ◽

Low Frequencies ◽

Limited Bandwidth

Interpretation of conventional land seismic data over a Permian-age gas field in Eastern Saudi Arabia has proven difficult over time due to low signal-to-noise ratio and limited bandwidth in the seismic volume. In an effort to improve the signal and broaden the bandwidth, newly acquired seismic data over this field have employed point receiver technology, dense wavefield sampling, a full azimuth geometry, and a specially designed sweep with useful frequencies as low as three hertz. The resulting data display enhanced reflection continuity and improved resolution. With the extension of low frequencies and improved interpretability, acoustic impedance inversion results are more robust and allow greater flexibility in reservoir characterization and prediction. In addition, because inversion to acoustic impedance is no longer completely tied to a wells-only low-frequency model, there are positive implications for exploration.

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High-Order AVO Inversion for Effective Pore-Fluid Bulk Modulus Based on Series Reversion and Bayesian Theory

Energies ◽

10.3390/en13061313 ◽

2020 ◽

Vol 13 (6) ◽

pp. 1313

Author(s):

Lei Shi ◽

Yuhang Sun ◽

Yang Liu ◽

David Cova ◽

Junzhou Liu

Keyword(s):

Bulk Modulus ◽

Seismic Data ◽

Pore Fluid ◽

High Order ◽

Bayesian Theory ◽

P Wave ◽

Seismic Exploration ◽

Inversion Method ◽

Fluid Identification ◽

Avo Inversion

Pore-fluid identification is one of the key technologies in seismic exploration. Fluid indicators play important roles in pore-fluid identification. For sandstone reservoirs, the effective pore-fluid bulk modulus is more susceptible to pore-fluid than other fluid indicators. AVO (amplitude variation with offset) inversion is an effective way to obtain fluid indicators from seismic data directly. Nevertheless, current methods lack a high-order AVO equation for a direct, effective pore-fluid bulk modulus inversion. Therefore, based on the Zoeppritz equations and Biot–Gassmann theory, we derived a high-order P-wave AVO approximation for an effective pore-fluid bulk modulus. Series reversion and Bayesian theory were introduced to establish a direct non-linear P-wave AVO inversion method. By adopting this method, the effective pore-fluid bulk modulus, porosity, and density can be inverted directly from seismic data. Numerical simulation results demonstrate the precision of our proposed method. Model and field data evaluations show that our method is stable and feasible.

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Computation of dry-rock VP/VS ratio, fluid property factor, and density estimation from amplitude-variation-with-offset inversion

Geophysics ◽

10.1190/geo2017-0621.1 ◽

2018 ◽

Vol 83 (6) ◽

pp. R669-R679 ◽

Cited By ~ 1

Author(s):

Gang Chen ◽

Xiaojun Wang ◽

Baocheng Wu ◽

Hongyan Qi ◽

Muming Xia

Keyword(s):

Reservoir Characterization ◽

Synthetic Data ◽

Pore Fluid ◽

Inversion Method ◽

S Wave ◽

Amplitude Variation ◽

Amplitude Variation With Offset ◽

Fluid Identification ◽

Fluid Property ◽

Avo Inversion

Estimating the fluid property factor and density from amplitude-variation-with-offset (AVO) inversion is important for fluid identification and reservoir characterization. The fluid property factor can distinguish pore fluid in the reservoir and the density estimate aids in evaluating reservoir characteristics. However, if the scaling factor of the fluid property factor (the dry-rock [Formula: see text] ratio) is chosen inappropriately, the fluid property factor is not only related to the pore fluid, but it also contains a contribution from the rock skeleton. On the other hand, even if the angle gathers include large angles (offsets), a three-parameter AVO inversion struggles to estimate an accurate density term without additional constraints. Thus, we have developed an equation to compute the dry-rock [Formula: see text] ratio using only the P- and S-wave velocities and density of the saturated rock from well-logging data. This decouples the fluid property factor from lithology. We also developed a new inversion method to estimate the fluid property factor and density parameters, which takes full advantage of the high stability of a two-parameter AVO inversion. By testing on a portion of the Marmousi 2 model, we find that the fluid property factor calculated by the dry-rock [Formula: see text] ratio obtained by our method relates to the pore-fluid property. Simultaneously, we test the AVO inversion method for estimating the fluid property factor and density parameters on synthetic data and analyze the feasibility and stability of the inversion. A field-data example indicates that the fluid property factor obtained by our method distinguishes the oil-charged sand channels and the water-wet sand channel from the well logs.

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Matrix-fluid decoupling-based joint PP-PS-wave seismic inversion for fluid identification

Geophysics ◽

10.1190/geo2017-0376.1 ◽

2019 ◽

Vol 84 (3) ◽

pp. R477-R487 ◽

Cited By ~ 2

Author(s):

Bing-Yi Du ◽

Wu-Yang Yang ◽

Jing Zhang ◽

Xue-Shan Yong ◽

Jian-Hu Gao ◽

...

Keyword(s):

Bulk Modulus ◽

Reservoir Characterization ◽

Joint Inversion ◽

Rock Physics ◽

Seismic Inversion ◽

New Method ◽

Converted Wave ◽

Fluid Identification ◽

Fluid Factor ◽

Fluid Detection

Seismic fluid identification is the main goal of current prestack seismic inversion. Various kinds of fluid indicators are used for fluid detection in industry today. However, the existing methods cannot always provide reliable fluid prediction owing to the insensitivity to fluid response and the lack of converted wave constraints. The equivalent fluid bulk modulus is an effective fluid factor based on matrix-fluid decoupling, which can provide persuasive evidence for fluid detection. Combining poroelasticity theory and matrix-fluid decoupling theory, we have deduced a new PS-wave linear amplitude versus offset approximation equation that provides estimations of equivalent fluid bulk modulus, rigidity, porosity, and density. Then, the joint inversion of PP- and PS-waves based on matrix-fluid decoupling was executed in a Bayesian framework with constraints from rock physics and well-log data obtaining elastic parameter estimation of high precision directly. We tested the new method on a synthetic example and field multicomponent data, and the results indicated that the estimated fluid factor matched with well-data interpretation and geology information because of adding converted wave information and avoiding indirect inversion error. This demonstrated that the new method can enhance the quality of fluid detection and provide reliable geophysical evidence for reservoir characterization.

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